1. Field of the Invention
The present invention relates generally to techniques for filtering signals, and more particularly, to techniques for filtering speech or other audio signals.
2. Background
In digital speech communication involving encoding and decoding operations, it is known that a properly designed filter applied at the output of the speech decoder is capable of reducing perceived coding noise, thereby improving the quality of the decoded speech. Such a filter is often called a post-filter and the post-filter is said to perform post-filtering. An adaptive post-filter is one in which the filter parameters are periodically modified to adapt to one or more local characteristics of the speech signal.
Adaptive post-filtering can be performed using a frequency-domain approach or time-domain approach. A known time-domain adaptive post-filter includes a long-term post-filter and a short-term post-filter. A long-term post-filter, which may also be referred to as a pitch post-filter, is used when the speech spectrum has a harmonic structure, for example, during voiced speech when the speech waveform is almost periodic. The long-term post-filter is typically used to attenuate spectral valleys between harmonics in the speech spectrum. In contrast, a short-term post-filter is typically used to attenuate the valleys in the spectral envelope, i.e., the valleys between formant peaks.
A known method for long-term post-filtering operates to increase the periodicity of the speech signal. For periodic signals, this increases the perceptual quality of the speech signal as the distortion between harmonic components is attenuated without affecting the harmonic components.
The operation of a typical all-zero long-term post-filter may be described by the following equation:y(n)=g·[x(n)+γ·x(n−L)],where x(n) is the input signal to the long-term post-filter, and y(n) is the post-filtered signal. The parameters g, γ, and L are typically adapted on a segment-by-segment basis to fit the local characteristics of the signal. The parameter γ controls the increase in periodicity (where L is the number of samples in the pitch period) and is typically derived from the input signal to the long-term post-filter to reflect the local periodicity of the signal, or as a function of a measure of periodicity provided by other means. For example, the parameter γ may be derived as a function of parameter(s) in a speech decoder such as pitch tap(s).
Similarly, the operation of a typical all-pole long-term post-filter may be described by:y(n)=g·[x(n)+γ·y(n−L)].
In order to avoid increasing the periodicity of non-periodic signals it is advantageous to effectively disable the long-term post-filtering during non-periodic signal segments, where the γ parameter typically exhibits fluctuations and thus can incorrectly introduce periodicity. In practice, this is often achieved by setting the γ parameter to zero if a measure of the local periodicity of the signal exceeds a certain threshold. However, because the measure of local periodicity itself can exhibit fluctuations, this method can still result in less than desirable results.
Also, as noted above, the long-term post-filter parameters are typically adapted on a segment-by-segment basis to fit the local characteristics of the speech signal. The changing of the long-term post-filter parameters at segment boundaries can result in the introduction of undesired distortion into the speech signal.
What is desired then, is a method for adaptive long-term post-filtering that addresses one or more of the aforementioned shortcomings of conventional techniques.